Large data sets are being used increasingly for everything from predicting consumer behavior to managing traffic conditions on the roadways. Continuing improvements in storage technology mean that many of the previous barriers to managing large data sets are disappearing, allowing even relatively small organizations to store and process large databases. More and more, metadata gleaned from analysis of data is also being generated, used, and stored. But data is only as useful as the ability to locate that data and analyze it. The increasing number of data sets in the world only increases the difficulty of determining which set of data is the right data for an individual or organization to analyze.
Traditional systems for managing sets of data are typically designed with an individual organization in mind. An organization may be able to access sets owned by the organization, but may be unable to share any of this information with outside entities or find data sets owned by others. Some traditional systems may allow users to buy data sets, but may not allow for negotiation on critical issues such as price and licensing. Even once a data set has been purchased, traditional systems may not provide a method to connect an organization that has acquired a data set with an analyst who can analyze the data set in order to draw meaningful conclusions. Accordingly, the instant disclosure identifies and addresses a need for additional and improved systems and methods for providing access to data sets owned by different entities.